University Of California, San Diego

NSF Awards · FY 2025 · 2025-07

This project supports research that advances national security and economic prosperity by seeking to enable the manufacture of high-performance composite structures through processes that are faster and less energy intensive. Thermoplastic polymers can be reheated, reshaped, welded, repaired, and recycled at end-of-life, leading to lighter aircraft, automobiles, and medical devices that consume less fuel and generate less waste than counterparts made from conventional thermosetting polymers. By seeking to deliver the fundamental science required to predict and optimize the manufacturing of thermoplastic composites, this award addresses the steep learning curve currently limiting their industrial adoption. An international team from the United States, Germany, and the National Aeronautics and Space Administration (NASA) will openly share data, simulation codes, and validated processing methods, accelerating innovation across multiple industrial sectors. The project will also strengthen the science and engineering workforce by providing research-driven training for undergraduate and doctoral students and offering a free public short course on integrated computational materials engineering, with materials available online for self-learning. In these ways, this effort directly serves the National Science Foundation’s mission to promote scientific progress and enhance the welfare of the United States. The central focus of this research project addresses a fundamental question: How do polymer morphology, interdiffusion, crystallization, and residual stresses during processing influence the interlaminar strength and fracture toughness of carbon fiber-reinforced thermoplastic composites? To answer this, the project looks to develop a physics-based, multiscale modeling framework that links processing conditions to interfacial mechanical properties in thermoplastic composites, enabling predictions and optimization of interlaminar strength and fracture toughness. Molecular dynamics simulations quantify polymer-chain interdiffusion, crystallization, and residual stress evolution at ply-to-ply interfaces under processing conditions representative of automated fiber placement, induction welding, and stamp forming. These interfacial properties inform micro-scale finite-element models that resolve heterogeneous crystallinity and coupled thermo-mechanical fields during consolidation. At the structural scale, cohesive-zone elements embedded within continuum damage mechanics capture interface bonding and subsequent debonding under service loads. To efficiently explore the extensive parameter space defined by time, temperature, and pressure, the team looks to develop a machine-learning surrogate model, identifying optimal processing windows that maximize mechanical performance while significantly reducing computation time. Advanced experimental characterizations across multiple length scales will validate the model predictions. This project is a collaboration between University of California-San Diego, Michigan Technological University, the National Aeronautics and Space Administration (NASA) and University of Wuppertal in Germany, which broadens modeling and experimental capabilities, ensuring the robustness of the developed toolset for certifying next-generation thermoplastic composite structures. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

The study of invariant geometries is a topic of fundamental importance in mathematics. These geometries arise naturally in many areas, including several complex variables (SCV), partial differential equations (PDE), and algebraic, complex, and differential geometry. This research project by the Principal Investigator is centered around a particular geometry - CR geometry - that arises in the study of SCV and complex geometry. It has deep and profound connections to central topics in mathematical and theoretical physics, including quantum field theory, general relativity, and string theory, as well as applications in systems engineering and control theory. The study of obstruction flatness, e.g., which has a prominent role in this project, has a direct link, via the Lorentzian Fefferman space, to the equations of motion in conformal gravity. The ideas and techniques that are needed for the investigations in this project come from a broad range of mathematical areas: complex analysis/geometry, PDE, and differential geometry; and, at the same time, the techniques and tools developed in this project will benefit these areas as well. The project will also provide interesting research topics and learning experiences for graduate students and postdocs. The seminar activity that will result from the project should be inspiring and stimulating for both students and other researchers. The goal of this mathematics research project is to study geometric and analytic aspects of invariant metrics and their potentials in complex analytic spaces, and related invariants in CR structures. The PI will investigate questions that are motivated by the classical and generalized Cheng-Yau and Ramadanov Conjectures concerning the Bergman metric and Bergman kernel, respectively, in strictly pseudoconvex domains in complex analytic spaces. He intends to work on the Cheng-Yau Conjecture for domains in Stein spaces with isolated singularities. The Ramadanov Conjecture, which asserts that strictly pseudoconvex domains with Bergman log flat boundaries are spherical, has been shown to fail in complex manifolds of dimension at least 3 (but holds true in dimension 2). This opens a compelling classification problem for domains with Bergman log flat boundaries that the PI intends to investigate. He also intends to study the asymptotic boundary behavior of invariant quantities such as the Bergman kernel, Bergman metric, and the Cheng-Yau solution to the complex Monge-Ampere equation. The investigations will elucidate how the boundary geometry influences analysis in complex spaces with boundaries. Additionally, the PI intends to pursue a theory for the Kohn Laplacian in domains on abstract CR manifolds. This is relevant to the local CR embedding problem in dimension 5. He also intends to continue his work on characterizing embeddability of compact CR 3-folds. The PI will investigate consequences of the global vanishing on a compact CR manifold of a higher order local invariant known as the obstruction function. This invariant is the obstruction to smooth extension to the boundary of the Cheng-Yau solution to the complex Monge-Ampere equation. In 3D, this invariant coincides with the trace at the boundary of the log-term in Fefferman's asymptotic expansion of the Bergman kernel and, hence, this problem is also connected with a strong form of the Ramadanov Conjecture. While the PI has made significant progress on the problem in 3D, it is still open in general. In higher dimensions, this problem is separate from the Ramadanov Conjecture, another problem that the PI intends to pursue. Additionally, he will investigate the relationship between the Bergman metric and the complete Kähler-Einstein metric in the setting of Stein spaces with singularities. A particular goal is to settle a generalized Cheng Conjecture in this context. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

ABSTRACT Mortality and morbidity are the most essential outcomes in patients admitted to the intensive care unit (ICU). Timely prediction can aid clinicians in making treatment decisions, optimizing resource allocation, improving outcomes, and managing patients’ and families’ expectations. Previously, our research team developed a multimodal deep learning model predicting mortality and morbidity among ICU patients by incorporating structured data (time-variant and time-invariant electronic health record [EHR] data) and unstructured data (clinical text and chest X-ray images). In this project, we aim to develop a multimodal foundation model that considers these three data modalities: chest X-ray (imaging), clinical notes (text), and structured data (EHR). The foundation model will then be fine-tuned to predict the probabilities of outcomes (mortality, morbidities, etc.) after different periods of time (within 4, 12, 24, or 48 hours, for example). Explanation of the predictions will be generated leveraging the multimodality of the model to help users assess its trustworthiness. To ensure that the design will meet the needs of care providers and minimize any ethical concerns, a co-design approach will be applied where clinicians, patient family members, ethics experts, and computer scientists will collaborate and iteratively develop the model using feedback from stakeholder engagement. The approach is divided into three tasks: (1) stakeholder engagement to aid in ethical and model design; (2) development of multimodal models, including using a foundation model architecture; and (3) external validation of models and assessment of algorithmic bias. The model may serve as a generalizable architecture for other multimodal models predicting clinical outcomes.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY To survive, individuals must appropriately adopt behaviors that fulfill their most pressing needs. This need prioritization requires the brain to flexibly switch between promoting certain behaviors while suppressing others based on different contexts. Feeding and socializing are motivated behaviors that are both critical for survival. During hunger, feeding must be prioritized over social behaviors, and an inability to do so could be detrimental. Though individuals must continuously integrate internal and external cues to select appropriate behaviors, feeding and social behaviors are often studied in isolation, leaving a critical gap in understanding the neural circuits connecting them. This knowledge gap hinders the development of treatments for neuropsychiatric conditions where social dysfunction and disordered eating frequently co-occur, including anxiety, depression, and autism spectrum disorder. To study social and affective behaviors in mice, the Smith lab developed the ‘social transfer of pain’ model, where ‘bystander’ mice display prosocial behaviors and acquire the pain state of an injured partner following a brief social interaction. Interestingly, food deprivation of bystanders suppresses these socio-affective behaviors. Furthermore, the nucleus accumbens (NAc) and paraventricular nucleus of the hypothalamus (PVH) are important for these social behaviors and receive inhibitory input from hunger-activated agouti-related peptide (AgRP) expressing neurons originating in the arcuate nucleus of the hypothalamus (ARC). Activation of ARCAgRP+ neurons drives feeding and suppresses social interactions, though the specific downstream regions inhibited by these neurons to mediate the effects of hunger on social behaviors have not been identified. To identify this circuit-level mechanism, this proposal will test the central hypothesis that activation of ARCAgRP+ projections to NAc and PVH suppresses socio-affective behaviors during hunger. This study will determine (1) how food deprivation alters neural activity during the social transfer of pain and (2) if ARCAgRP+ projections to the NAc and PVH are necessary for the hunger-induced suppression of socio-affective behaviors. The first aim will be tested using immunohistochemistry to determine if food deprivation increases activation in hunger-signaling ARCAgRP+ neurons and decreases activation in the NAc and PVH. Then, to test this in vivo, fiber photometry will be used to record activity of ARCAgRP+ à NAc and ARCAgRP+ à PVH projections in food-deprived bystanders during the social transfer of pain. The second aim will use optogenetic inhibition to test the necessity of these projections, whereby inhibiting activity in these projections is expected to prevent the hunger-induced suppression of socio-affective behaviors. This research will reveal the neural mechanism by which hunger modulates social and affective behaviors, providing critical insights on how motivated behaviors are prioritized in the brain. This is an essential step in developing novel therapeutics for social deficits and disordered eating in neuropsychiatric conditions.

NIH Research Projects · FY 2026 · 2025-06

SUMMARY Spatial omics are revolutionizing cancer biology by uncovering the intricate molecular architecture of tissues and solid tumors. They provide unprecedented insights into the tumor microenvironment, cell-cell heterogeneity, and interactions, helping map in situ cancer-associated cellular reprogramming. Additionally, spatial omics complement traditional histology techniques, adding novel molecular layers to the interrogation of solid tumors. Metabolism has re-emerged as a key factor in cancer and cancer therapy. While metabolic reprogramming, and particularly the Warburg effect, have been traditionally recognized as cancer hallmarks, recent developments reveal the regulatory roles of metabolites and their functional impacts on cancer cells, immune cells, and other contributors to the tumor microenvironment. Addressing the need for spatial biology and understanding metabolism of cancer in situ, spatial metabolomics was established as a technology able to detect metabolite abundances in tissues at near-single-cell resolution. Cancer biology is a key application of spatial metabolomics, as evidenced by numerous publications and grants in this field. It has provided insights into multiple applications in cancer research, including mapping metabolism of the solid tumor microenvironment at near-single-cell resolution, resolving metabolism of cancer cells and other cell types, conducting drug disposition studies for bioactive drug metabolites, correlating metabolic responses to detected drugs and metabolites in a dose- dependent manner, and performing molecular histology. Spatial metabolomics, commonly performed using imaging mass spectrometry, generates large and complex datasets, making data analysis critical for interpreting the data in cancer research and translating findings into actionable insights. To address this challenge, we previously developed METASPACE, a free and open-source cloud software platform for spatial metabolomics. METASPACE addresses a key problem in the field—metabolite identification—and provides a broad spectrum of features for experiment planning, quality control, data visualization, analysis, management, and sharing. The overarching goal of this project is to advance METASPACE, increase its utility, and accelerate the adoption and impact of spatial metabolomics in cancer research.

NIH Research Projects · FY 2025 · 2025-06

Project Summary Human papilloma virus negative (HPV-) head and neck squamous cell carcinoma (HNSCC) is associated with high mortality and current curative treatment options incur significant morbidity. Despite activity in recurrent/metastatic settings, PD-1 inhibitors have low response rates of 14-20% in previously untreated, locally advanced HNSCC when given in the neoadjuvant setting, and recent Phase III trials demonstrate no benefit when a PD-1 inhibitors are combined with chemotherapy and broad field radiation to primary tumor and draining lymph node basins. We recently reported that nodal irradiation or surgical removal of draining lymph nodes completely blocks the anti-tumor activity of PD-1 inhibitors, indicating a key role for tumor draining lymph nodes in facilitating primary tumor response to immunotherapy. In support of these findings, a Phase I trial of immunoradiotherapy (IRT) using PD-1 inhibitors combined with lymphatic sparing, stereotactic radiation (SBRT) demonstrated a remarkable 67% complete pathologic response rate in HNSCC patients. Using orthotopic, syngeneic murine models of HPV- HNSCC, we found that IRT with sequenced, tumor directed, lymphatic sparing radiation followed by PD-1 inhibition produces a dramatic, synergistic, and durable tumor response supported by migration of immune cells to tumor draining sentinel lymph nodes (SLN) and development of clonal T cell responses in both tumor and SLN. Mechanistically, simple surgical disruption of lymphatic channels connecting primary tumor and SLN completely blocks response to IRT, and we specifically found that IRT modulates the phenotype and migration of activated dendritic cells (DCs) from tumor to SLN that are critical to IRT driven anti- tumor immune responses. Our central hypothesis is that activation and migration of activated DC from tumor to sentinel lymph node is key to promote anti-tumor immunity and clinical responses to IRT in HPV- HNSCC patients. We also hypothesize that cross-presenting, activated DC migration can be enhanced to improve HPV- HNSCC therapeutic response. To explore these hypotheses we will 1) define the functional state of dendritic cells in tumor and draining sentinel lymph nodes in the context of a Phase II clinical trial of sequenced neoadjuvant, lymphatic sparing SBRT followed by immunotherapy in HPV- HNSCC patients, and 2) leverage activated dendritic cell migration to sentinel draining lymph nodes to optimize adaptive immune responses during immunotherapy and immunoradiotherapy in mouse models of HPV negative HNSCC Completion of these aims will elucidate the role of specific, activated, migratory dendritic cells in coordinating anti-tumor immune responses in response to IRT in HPV- HNSCC patients and define dendritic cell immune signatures in patients treated with IRT in HPV- HSNCC. We will also design novel therapeutic strategies by leveraging enhanced dendritic cell function and migration to immunologically intact draining lymph nodes in HPV- HNSCC. This project can inform and guide novel therapeutic approaches based on enhancing activated dendritic cell migration in HNSCC and other solid tumor types.

NSF Awards · FY 2025 · 2025-06

This project's goal is to help communities better support the facilitation of audience engagement and information sharing in real-time social media. The real-time and ephemeral nature of livestreaming, social virtual reality, and other real-time platforms raises new concerns around community management relative to existing science on supporting online communities. Drawing parallels between real-time social media and best practices in conversational facilitation and conflict resolution, the project team will develop methods and tools to help community leaders identify behaviors that diverge from community norms and provide guidance (and when needed, warnings) interventions to encourage participants to engage in ways that serve the community's goals. Conducting this research will advance scientific knowledge around building strong online communities while providing many educational and outreach opportunities in computer science, interaction design, and real-time social media. The research plan is structured around two main aims. The first aim is to develop tools that support hosts of real-time social media in facilitating audience participation. This includes modeling audience behaviors and developing tools that allow community members to guide participants toward adhering to community norms. The second aim is to develop auditing mechanisms to identify potential biases in the facilitation decisions made by both community leaders and the tools they use, and to provide mechanisms and information that help community members to contest those decisions. Together the research will develop a deeper understanding of community behavior in real-time social media, along with practices and tools that operate transparently for both community leaders and participants. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

Developing intelligent machines capable of reasoning efficiently and robustly at a human level is of critical importance across numerous real-world domains, including healthcare, finance, entertainment, and beyond. Current large language models represent some of the most powerful intelligent systems created to date, demonstrating remarkable abilities in text generation and human-like conversation. However, these models often fail in surprising ways, particularly when confronted with complex reasoning challenges such as multi-step logical or mathematical inference or planning action sequences for tasks in physical environments. In contrast, humans approach reasoning in a fundamentally different way. Equipped with a mental model of the world, humans form a consistent understanding of their environment, enabling robust and deliberate reasoning. This world model allows us to simulate alternative actions, predict their outcomes, and refine our reasoning based on these simulations. This project aims to develop the next-generation machine reasoning capabilities by systematically incorporating the key concept of “world model” into the design, training, and application of new reasoning models. The research will deliver a comprehensive set of innovative algorithms and models to elevate machine reasoning to a new level of flexibility, consistency, and robustness. Furthermore, the project will support the development of new undergraduate and graduate courses, provide mentorship to students in artificial intelligence research, and engage in extensive outreach efforts with K-12 students, the general public, and industry professionals. To achieve these goals, the project will formulate and implement a new machine reasoning paradigm centered on world models. The research will deliver systematic innovations in three key areas: (1) new inference algorithms that induce the internal world model within pretrained large language models and conduct principled strategic planning that mirrors the deliberate reasoning in humans; (2) new learning methods with rich forms of experience beyond text, including embodied interactions for physical world knowledge and self-synthesized data for continual reasoning skill enhancement; (3) a new unified multi-modal world model for more comprehensive world understanding and efficient reasoning simulation in a unified latent representation space. These advances will be seamlessly integrated, representing a significant step forward in the pursuit of human-level reasoning capabilities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

Sources of gamma rays —- an extremely energetic form of light —- are needed for national security, nuclear waste analysis, and medical isotope production, as well as for fundamental studies of matter and antimatter creation from light alone. This joint project between the University of California San Diego, General Atomics, and Extreme Light Infrastructure - Nuclear Physics (ELI-NP) in Romania will demonstrate a key step towards developing such sources. Powerful lasers uniquely available at ELI-NP will be used to generate strong magnetic fields and ultra-energetic electrons inside a plasma, leading to efficient gamma-ray emission. Hands-on training will be provided to U.S. students and scientists through experiments at the cutting-edge ELI-NP laser facility in Romania, helping to build a skilled workforce in high-intensity laser science. The project will also strengthen scientific collaboration between the U.S. and Romania, offering access to capabilities not currently available in the U.S. while providing complementary expertise to Romanian partners. The project will examine how collective plasma phenomena enhance energy transfer from an intense laser pulse to plasma electrons. Structured targets developed at General Atomics will be employed to independently control two key effects: the generation of a strong azimuthal magnetic field and the laser phase velocity. These effects are expected to enable frequency matching between the oscillating, forward-moving electron and the laser field, while mitigating frequency detuning that would otherwise limit energy gain. The resulting increase in electron energy is anticipated to produce enhanced gamma-ray emission, primarily driven by the plasma magnetic field. The underlying physics will be explored through kinetic simulations and validated experimentally at ELI-NP, where a sequence of two laser pulses will be used to create and probe the structured plasma. The gamma-ray signal will serve as a direct observable of the enhanced energy transfer. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-06

Metabolic dysfunction-associated steatotic liver disease (MASLD), encompassing adult and pediatric steatohepatitis (MASH), represents a burgeoning public health challenge linked to nutritional imbalances. However, the escalating prevalence of MASLD cannot be attributed solely to diet and obesity. Our research has unveiled that specific environmental toxicants synergize with high-fat diets (HFD) to expedite MASH progression in mice, leading us to hypothesize that exposure to unidentified environmental pollutants during early life may predispose individuals to early-onset MASLD/MASH. One likely suspect is triclosan (TCS), a pervasive antiseptic and disinfectant that humans encounter through an array of consumer products and environmental sources. TCS has been detected in the plasma of adolescents, pregnant women, and breast milk. Exposing obese or diabetic adult mice to TCS concentrations mirroring human exposure triggers characteristic signs of MASLD-related toxicant-associated steatotic liver disease (TASLD) and steatohepatitis (TASH), including steatosis, hepatocyte damage, inflammatory infiltrates, and liver fibrosis. TCS enhances HFD-induced MASLD by suppressing the expression of fibroblast growth factor 21 (FGF21), thereby leading to abnormal expression of enzymes associated with amino acid and fatty acid synthesis. Given the evidence of TCS accumulation in breast milk, we conducted experiments involving mating mice exposed to dietary TCS, which resulted in efficient lactational TCS transmission to newborn pups. This induced rapid onset hepatosteatosis, endoplasmic reticulum (ER) stress, inflammation, and fibrosis, all mechanistically linked to elevated expression of transcription factors ATF4 and PPARα. Lactational TCS exposure also led to intestinal barrier disruption, akin to the pathology observed in mice fed high fructose (HF) diets. In conjunction with hepatic ER stress, this disruption led to MASH development. Notably, targeted activation of barrier-protective STAT3 and YAP signaling in enterocytes mitigated lactational TCS-induced liver pathologies. These findings bear clinical significance, because children and adolescents are primary consumers of fructose-enriched, energy-dense diets and are subject to both lactational and environmental TCS exposure. To explore the pathogenic potential of this combination, we will employ mouse models in this MPI application, combining Dr. Tukey’s expertise in TCS-driven MASLD/TASLD with Dr. Karin’s expertise in studying the impact of fructose and energy-dense diets on MASLD/MASH and barrier integrity. We aim to investigate the mechanisms by which lactational TCS heightens the risk and severity of HFHFD-induced liver disease, with a focus on the role of ER stress effectors PERK and ATF4, along with the identification of the cell types in which they operate. Additionally, we will examine the protective roles of FGF21 and the barrier- fortifying cytokine IL-22, primarily active in enterocytes, as well as the hypothesis that lactational TCS exposure establishes an "epigenetic memory" that accelerates TASLD progression to MASH in later life. This project will yield novel mechanistic insights into early-life toxicant exposure.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Human immunodeficiency virus (HIV) lacks a vaccine despite being a global priority. HIV poses a unique challenge to vaccine design, as many characterized broadly neutralizing antibodies (bnAbs) possess unusually high frequencies of somatic hypermutations. To generate potential bnAbs, B cells must undergo iterative rounds of affinity maturation and selection within germinal centers (GCs). Our lab and collaborators have made significant contributions to the HIV vaccine field. These contributions include sequential immunization strategies to efficiently prime bnAb-precursor B cells to enter GCs and to increase the diversity and length of the GC. Despite our success with these regimens in preclinical models, our understanding of sequential immunization strategies impacts to the GC microenvironment is lacking. We hypothesize that the formulation of an immunization regimen i) can directly influence antibody-secreting and memory B cell differentiation and ii) this is driven by the remodeling of the GC microenvironment. These hypotheses will be tested using different mouse models with sequential immunization strategies designed to track antigen-specific GC B cells and stromal cells. A combination of multiparameter flow cytometry, high resolution microscopy, RNA-sequencing, ELISA, and ELISpot techniques will be used throughout the proposed work. These investigations including the studies of the stromal network underlying the GC microenvironment is a largely underappreciated facet for the generation of adaptive immunity. This work has the potential to reveal novel considerations for the formulation of HIV vaccines with the capacity for long-term retention of B cells within GCs to generate bnAbs.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Gastrointestinal stromal tumors (GIST) are most often driven by oncogenic KIT mutations and are treated with FDA-approved tyrosine kinase inhibitors [TKIs, including imatinib (IM)] that target constitutively active KIT. However, these drugs are only modestly effective. Even in the treatment naïve setting, ≤10% of patients have complete responses to treatment. Thus, TKIs do not kill every tumor cell despite the absence of secondary resistance mutations in KIT. Data from our lab demonstrates that treatment naïve KIT mutant GIST contain subpopulations of IM-resistant “persister” tumor cells that lack KIT, but do express Kvβ1.1, the protein product of the KCNAB1 gene. Kvβ1.1 regulates the channel activity of pore-forming α-subunits in voltage-gated potassium channels (VGKCs) that allow cells to modulate plasma membrane potential and cell volume homeostasis that, in turn, critically affects processes central to cancer biology (cell cycle regulation, cell migration and invasion). FDA-approved in 2010 for treatment of multiple sclerosis, 4-AP (fampridine) blocks VGKCs to improve motor skills. We now find that 4-AP synergizes with IM in vitro and in a murine model to better treat KIT mutant GIST vs. IM alone. Our preliminary evidence strongly supports two Central Hypotheses: 1) high Kvβ1.1 protein (or high KCNAB1 mRNA) expression unequivocally identifies TKI-resistant persister cells in KIT mutant GIST; and 2) combined with KIT targeting by IM, the VGKC complex is a novel therapeutic target for eradicating both TKI-sensitive and TKI-resistant tumor cells in KIT mutant GIST. Our Overall Objectives are to: 1) determine the safety and tolerability and to assess the radiologic and pathologic efficacy of IM with 4-AP in a Phase 1 (3+3 design) neoadjuvant trial of 9-18 patients with treatment naïve KIT exon 11 mutant GIST (Aim 1); 2) validate pretreatment Kvβ1.1 protein or KCNAB1 mRNA expression as biomarkers predicting treatment response (Aim 1); 3) determine how genetic and pharmacologic modulation of VGKCs impacts cancer-relevant cell biology to define mechanisms mediating VGKC regulation of GIST aggressiveness (Aim 2); and 4) study KIT mutant GIST tumor prognosis (Aim 3). At our high-volume “GIST Center of Excellence” at the NCI- designated Moores Comprehensive Cancer Center at UC San Diego, we have united eight distinct investigators and their teams towards achieving a common goal: to drastically improve outcomes in KIT mutant GIST. This multi-disciplinary team includes expertise in: i) GIST surgical & medical oncology (Sicklick & Fanta); ii) conduct of clinical trials (Sicklick, Fanta, Messer); iii) radiology & mRECIST measurements (Hahn); iv) GIST pathology (Hosseini); v) GIST cellular & molecular biology (Sicklick); vi) computational biology & single cell omics (Mesirov & Tamayo); vii) VGKC biology (Joiner); and viii) biostatistics (Messer). Our project will: 1) test a new combination strategy for treating KIT mutant GIST; 2) have immediate applications for a follow-on Phase 2 clinical trial to test efficacy in for treating GIST; and 3) validate novel ways to eliminate persister cells that could be paradigm shifting, and ultimately lead to a cure for GIST.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY Despite the wide use of glucocorticoids to manage symptoms in people with solid tumors, these steroids have been linked to tumor progression and metastasis especially in breast cancers that are negative for estrogen receptor. Here we will investigate how extracellular vesicles produced by breast cancer cells cause an overproduction of glucocorticoids, the “stress hormones”, and how this affects normal cells in the body to facilitate breast cancer metastasis. The goals of this study are: (1) to identify the mechanism by which cancer cell-produced extracellular vesicles enhance glucocorticoid production; (2) to determine the effect of activated glucocorticoid signaling at the whole body level; and (3) to explore the use of clinically available pharmacological inhibitors of glucocorticoids in cancer treatment. In Aim 1, we will determine the mechanism(s) through which extracellular vesicles from breast cancer cells lead to an overactivation of the neural control pathway that is responsible for the production of glucocorticoids. We will focus on pre-selected microRNAs in the extracellular vesicles for their role in regulating this central control pathway. In Aim 2, we will determine the gene regulatory effects of glucocorticoid signaling that is induced at the whole body level. We will focus on the functional role of those genes involved in the formation of pre- metastatic niches especially in the lungs, and will dissect the immunomodulatory and non-immune effects of cancer-induced glucocorticoid signaling. In Aim 3, we will evaluate the anti-tumor and anti-metastasis effects of clinically approved adrenal steroidogenesis inhibitors and glucocorticoid receptor antagonists, either as monotherapy or in combination with a first-line treatment for breast cancer. Next, we will compare levels of selected markers in the blood of breast cancer patients and non-cancer controls, as well as the associations of these blood markers with indicators of glucocorticoid signaling in tumor tissues. The proposed project will provide a new understanding of the dynamic and reciprocal communication between cancer and host at the whole body level. We will establish the mechanisms through which tumor-derived factors, such as extracellular vesicles, directly influence the neuroendocrine pathway that controls glucocorticoid production, and will develop a high-resolution map for the tissue-specific and cell type-specific target genes regulated by glucocorticoids. Results from this project may establish clinical evidence for the investigated mechanisms and explore if we may select breast cancer patients who will benefit from adding an anti-glucocorticoid therapy to their anticancer treatment.

NIH Research Projects · FY 2025 · 2025-06

Summary/Abstract Traditional models of visual information processing propose that stable perceptual and mnemonic representations are supported by persistent activity in neurons that are selective for relevant stimulus features. However, there is an emerging focus on the importance of reducing redundancy in neural codes to achieve more efficient processing. For example, the visual system adapts to overall lightness levels and to frequently encountered stimuli, allowing neural codes to maintain a useful dynamic range and to expend less energy encoding expected stimuli. In addition to dynamics induced by recent stimulus history, recent work in machine learning and in animal model systems reveals that codes also drift over short and long time scales, often while preserving population-level geometric relationships between different stimulus representations. While many factors likely contribute to this set of phenomena, here we focus on the general hypothesis that dynamics induced by stimulus history and other factors support efficient yet error-tolerant codes. For example, recent work in our lab suggests that the perceptual distortions induced by adaptation (e.g. the classic motion after-effect) are offset by a flexible decoding scheme that utilizes a prior for temporal stability to compensate. Short-term dynamics, particularly during visual working memory, at least partially reflect a reduction in the complexity of representations so that only the most behaviorally relevant aspects of sensory information are retained to guide behavior. Finally, long-term dynamics, or representational drift, may reflect a refining of neural codes to support increasingly sparse information processing that is still robust to interference. In the present proposal, we build on this recent empirical and theoretical work to evaluate the functional role of neural dynamics driven by different factors across different time scales. We first test how the flexibility of Bayesian read-out rules allows the visual system to counter the effects of stimulus history to produce continuous and robust representation even in the face of internal and external noise. We then use recurrent neural networks (RNNs) with different processing constraints to show that a drive toward sparser, and more energy efficient, representations is sufficient to induce short and long-term drift in neural codes. Guided by these modelling efforts, we will evaluate the impact of drift on neural codes as measured in human visual cortex using functional magnetic resonance imaging (fMRI) and psychophysics, with a focus on testing hypotheses about the impact of drift on the dimensionality and robustness of feature-selective activation patterns. Collectively, this work will challenge traditional theories of perceptual inference, attentional selection, and working memory that are based on the notion of stable neural codes by providing novel insights into the functional role that pervasive neural dynamics play in visual information processing.

NSF Awards · FY 2025 · 2025-06

Magnetism is a fundamental enabling technology that underpins modern electronics, data storage, transportation, and medical diagnostics. Advancing knowledge in this field is critical for continued innovation, and a summer school will significantly contribute by providing participants with intensive training at the forefront of magnetics research. The 2025 IEEE Magnetics Society Summer School is a week-long international educational program focused on nanomagnetism. It will be held June 21–25, 2025 at the Center for Memory and Recording Research (CMRR) at the University of California, San Diego. Lectures by world-leading experts will expose students to state-of-the-art experimental techniques and theoretical developments, broadening their understanding beyond what is available at their home institutions. Through interactive discussions and opportunities to present their own research, students will sharpen their critical thinking and scientific communication skills. This immersive intellectual environment is designed to spark new research ideas and collaborations among the participants, as they exchange perspectives and learn directly from pioneers in magnetism. By cultivating deeper expertise and a network of professional relationships, the summer school will empower these early career researchers to make novel contributions to magnetics research, thereby propelling the field forward. The summer school will have strong emphasis on global engagement and knowledge dissemination. By bringing together students from around the world the program broadens participation in STEM and encourages interactions within the magnetics and other research communities. Attendees receive financial support to attend, removing economic barriers and ensuring that selection is based on talent and potential. The international students and faculty create a global network of peers and mentors, fostering cross-cultural collaboration and long-term professional relationships that can drive future scientific advancements. After the program, participants will share the knowledge and skills gained with colleagues at their home universities through seminars, research collaborations, and mentoring, thereby multiplying the impact. Lecture materials and resources from the school will be made freely available online, allowing students and educators beyond the event to benefit from the content. The participation of industrial partners will contribute to industry-academia knowledge exchange and provide internship and R&D employment opportunities. In the long term, strengthening skilled magnetics researchers will benefit society by catalyzing innovations in technologies that rely on magnetism, spanning energy, communications, and information storage. It will also help build a more globally connected scientific workforce. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

The nervous system interprets a wide range of signals to help control how humans move. This process involves specialized circuits in both the brain and spinal cord. Although tools are available to measure circuits in the brain, it is still challenging to measure activity in the spinal cord. This project will develop new probes for studying the spinal cord that are small, flexible, and can study multiple regions of the spinal cord at the same time. Overall, the project will address how to engineer spinal cord probes that can be precisely positioned to target specific spinal neural circuits at different sites and depths. In addition to its scientific impact, this project will develop student talent in engineering. An “Adopt-a-Student” program will be established to introduce middle and high school students to STEM fields. This project will also enhance undergraduate education by implementing hands-on training and mentoring through new classroom laboratory modules and team projects. This project will accelerate the development of minimally invasive, multi-modal probe technologies for acute and chronic spinal interfacing. High-aspect ratio, dual-modality, mechanically flexible probes will be fabricated that deliver a small footprint of less than 10 μm, low electrical impedances, and sub 20 dB optical losses from source to tip that allow efficient activation of opsin-labeled neurons, and simultaneous high signal-to-noise ratio electrophysiological recordings with single-unit recording capacity at the same site. Detachable printed circuit board templates will be fabricated for the first time, providing a “GPS” for probe placement, high-fidelity electrical/optical connections, and the ability to seal a laminectomy covering multiple spinal segments and both sides of the spinal cord. The findings from this project will lead to scalable manufacturing solutions for high-density, multi-modal arrays of individually addressable probes that leverage global positioning via computer vision-assisted robotic insertions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Methamphetamine (METH) past-year use prevalence has doubled since 2015 (from 0.51% to 1.11%), as have METH-involved deaths. METH use represents a significant threat to public health and a challenge to treatment efforts, as METH use is associated with substantial negative impacts on mental and physical health. There are currently no effective pharmacological treatments for METH use disorder (MUD), and cognitive and behavioral therapies remain difficult to access for people with MUD. Co-use of other substances (polysubstance use) and high likelihood of developing substance use disorders are central features of METH use that increase risk for poor treatment outcomes and contribute to METH’s disproportionate public health burden. Recent population- level data shows that 78.2% of MUD treatment cases involve other substance use disorders. To date, studies have focused on effects of METH use in combination with one or two other substances (e.g., opioids), but other substances are highly prevalent among METH users and complicate the understanding of METH’s influence on mental health, physical health and the course of METH treatment. This project aims to fill gaps in the current literature by identifying “types” of polysubstance use with METH in the US, which may better predict outcomes and inform the implementation and development of MUD interventions across treatment settings. This project will be supported by an interdisciplinary mentorship team with relevant and complimentary expertise and the rich substance use research and training environment at the University of California, San Diego (UCSD) HIV Neurobehavioral Research Program (HNRP). The proposed R36 will utilize multivariate mixture models, large computational structures, and two large, publicly available data sources: National Survey on Drug Use and Health (NSDUH, 2015-2022) and Treatment Episodes Data Sets (TEDS, 2018-2021), which are published and maintained by the Substance Abuse and Mental Health Services Administration. This proposal specifically aims to 1) provide an updated epidemiological understanding of polysubstance use with METH in the US, 2) identify clinically distinct subpopulations of people who use METH and examine how these differ in demography, medical and mental health, treatment history and access, and MUD treatment outcome, and 3) identify common histories of substance use initiation prior to METH and examine their relationship with demography, current medical and mental health, treatment history and access, and current MUD. These aims are consistent with the National Institute on Drug Abuse’s strategic plan to identify what substances are being used in combination, by whom, and how these combinations may influence differential outcomes. Completion of this R36 proposal will allow me to fulfill the doctoral dissertation requirements for a PhD in clinical psychology and expand my foundational research skills, which I aim to leverage in building my career as an independent investigator, focused on understanding “real world” substance use and its impact on mental and physical health.

NIH Research Projects · FY 2025 · 2025-06

eDyNAmiC (extrachromosomal DNA in Cancer) Human genes are arranged on 23 pairs of chromosomes, but in cancer, tumour-promoting genes can free themselves from chromosomes and relocate to circular, extrachromosomal pieces of DNA (ecDNA). These ecDNA do not follow the normal “rules” of chromosomal inheritance, enabling tumours to achieve far higher levels of cancer-causing oncogenes than would otherwise be possible, and licensing cancers with a way to evolve and change their genomes to evade treatments at rates that would be unthinkable for human cells. The altered circular architecture of ecDNAs also changes the way that the cancer-causing genes are regulated and expressed, further contributing to aggressive tumour growth. These unique features make ecDNA-containing cancers especially aggressive and difficult to treat. Cancer patients whose tumours harbour ecDNA have markedly shorter survival. Despite being first seen over fifty years ago, the critical importance of ecDNA has only recently come to light, and the scale of the problem is substantial. ecDNAs are present in nearly half of all human cancer types and potentially up-to a third of all cancer patients. The collective current understanding of how ecDNA form, how they function, how they move around the cell, how they evolve to resist treatment, how they impact the immune system, and how they can be effectively targeted are lacking. We bring together an internationally recognized, pioneering interdisciplinary team of cancer biologists, geneticists, computer scientists, evolutionary biologists, mathematicians, clinicians, and patient advocates to boldly create novel insights and resources and to provide transformative solutions to one of Cancer’s Grand Challenges. A core team of experienced and productive ecDNA investigators will work with new investigators in the ecDNA and cancer fields to bring completely new perspectives and approaches to this daunting challenge. By bridging cutting-edge and diverse approaches and insights from cancer genomics, yeast genetics, epigenomics, artificial genome synthesis, longitudinal patient tracking, combinatorial and machine learning algorithms, mathematical modelling, immunobiology, and innovative chemistry we will develop a new understanding of the role of ecDNA in cancer, and we will find new ways to drug the undruggable. This bold programme, which consists of 7 work packages and a committed international infrastructure, generates new and unusual collaborations that would simply be impossible under any other type of funding mechanism. Our programme endeavours to foster bold innovative solutions to one of the hardest problems in cancer and to one of the greatest challenges facing cancer patients.

NIH Research Projects · FY 2026 · 2025-06

Project Summary Marfan Syndrome (MFS) is a genetic disorder with a prevalence of ~1 in 5,000 people. Aneurysms in the ascending aorta are the most serious manifestation of the condition and can lead to sudden death due to spontaneous rupture. The aneurysms are due in part to increased oxidative stress in the smooth muscle cells of the aortic wall. Existing medical treatments are not disease-modifying and are only partially effective. Surgical aneurysm repair is the only proven method to prevent death. Cobinamide is the penultimate precursor in the biosynthesis of vitamin B12 (cobalamin). We have shown recently that cobinamide is a powerful and versatile antioxidant, more potent than other well-known antioxidants and able to neutralize both reactive oxygen and reactive nitrogen species. When administered as bis(histidyl)cobinamide in drinking water, cobinamide prevented aortic dilation and abolished oxidative stress and pathological changes in the aorta of mice with a mutation in fibrillin-1, analogous to mutations that occur in Marfan patients. Cobinamide thus has the potential to be a disease-modifying treatment for MFS. Under a Phase I SBIR grant, we found that bis(histidyl)cobinamide has low bioavailability, only 0.8% was absorbed after oral administration. The goal of the current project is to increase intestinal absorption of cobinamide to make it a more practical therapy for conditions like MFS where long-term treatment is needed. This will be accomplished by varying the ligands coordinated to the central cobalt atom of cobinamide and by using permeation enhancers. Bis(histidyl)cobinamide is hydrophilic with a low log P value, retarding its movement across cells. Hydrophobic ligands can increase the hydrophobicity/lipophilicity of the resulting cobinamide complex, and we found that a phenyl-containing ligand increased cellular uptake of cobinamide and cobinamide bioavailability ~2-fold compared to bis(histidyl)cobinamide. We now plan to test a variety of hydrophobic ligands, with the intent of finding ligands that increase cobinamide permeation through a human intestinal tissue model (EpiIntestinalTM) 4-5-fold compared to bis(histidyl)cobinamide. We will then combine these liganded cobinamide complexes with a permeation enhancer. Chitosan, a well-known permeation enhancer, increased cobinamide absorption across mouse gingiva, and salcaprozate sodium, another permeation enhancer, increases intestinal vitamin B12 (cobalamin) absorption. We will test these and other enhancers, with the overall goal to increase cobinamide permeation through EpiIntestinalTM by 8-10-fold compared to bis(histidyl)cobinamide. We will then evaluate bioavailability of the top performing cobinamide formulations (complex-enhancer combinations) in rats, with the goal of finding one or more formulations that yields a bioavailability of ≥6% in male and female animals. A number of drugs have bioavailabilities ranging from 1-10%.

NIH Research Projects · FY 2025 · 2025-06

ABSTRACT Neurons serve as foundational units underlying neural computations. The computational capacity of individual neurons arises, in part, from their extensive dendritic arbors that are capable of nonlinearly integrating and transforming synaptic inputs. However, dendrites are not uniform and can be categorized into discrete compartments that have distinct anatomical and biophysical properties that influence how synaptic inputs are integrated to regulate somatic activity. As a result, different dendritic compartments may favor distinct synaptic organization motifs that confers them with unique computational properties. Yet, our understanding of how synapses are functionally organized along different compartments of the dendritic arbor in the intact brain remains limited, presenting a gap in our comprehension of how synaptic and dendritic function contribute to neural computation. To address this gap, the research proposed here will use cutting-edge imaging approaches and causal manipulations to investigate the compartment-specific functional organization of synaptic inputs along the dendrites of layer 2/3 pyramidal neurons in behaving animals, as well as the mechanisms that shape this organization over the course of learning. Specifically, Aim 1 will characterize how synapses from different input regions are spatially and functionally organized along apical and basal dendrites in behaving animals. Next, Aim 2 will determine the activity-dependent rules shaping synaptic plasticity in apical and basal dendrites as animals undergo learning. Lastly, Aim 3 will examine how the spatiotemporal dynamics of neuromodulatory signaling conveying behaviorally relevant information interacts with ongoing synaptic and neural activity to regulate synaptic plasticity along the apical and basal dendrites during behavior. Accomplishing the proposed work will provide important insights into how different dendritic compartments integrate and transform incoming inputs to perform neural computations and how these processes adapt through learning. In addition, the applicant will receive extensive technical training in state-of-the-art in vivo two-photon, confocal, and electron microscopy methods, as well as genetic and optogenetic manipulations, under the guidance of his primary mentor Dr. Takaki Komiyama and his external advisory committee consisting of Drs. Mark Ellisman, Byungkook Lim, Mikio Aoi, and Thomas Hnasko. This strong mentorship in combination with the numerous professional development resources and rich research environment at the University of California, San Diego will benefit the applicant’s research and transition to an independent research program focused on the dendritic and synaptic mechanisms underlying neural computation in health and disease.

NIH Research Projects · FY 2025 · 2025-05

PROJECT SUMMARY/ ABSTRACT Chronic low back pain (cLBP) is the most common musculoskeletal pain condition associated with substantial inter-individual variability. Further, major depressive disorder (MDD) is comorbid in up to 46% of individuals with cLBP, which is related to worse pain and depression severity, disability, and quality of life, and poorer response to existing treatments compared to cLBP alone. MDD is itself a heterogenous condition, and thus any association with cLBP also likely varies between individuals. While the biopsychosocial model has been helpful for identifying biological, psychological, and social processes associated with cLBP, as well as helping to explain the overlap between cLBP and MDD, a major challenge in optimizing the treatment is identifying which factors, and in which combination, are most related to an individual’s unique pain experience. In response to the Notice of Funding Opportunity for Understanding Individual Differences in Human Pain Conditions, the proposed research will generate individualized prediction models of momentary pain intensity among 150 adults with cLBP+MDD (Aim 1). This will be accomplished by a combination of ecological momentary assessments (EMA) and whole-health metrics obtained from wearables, all processed with a robust machine learning (ML) pipeline previously validated in our laboratory. We hypothesize that personalized prediction models of pain variability using ML algorithms will be feasible in at least 80% of participants, achieving ~80% prediction accuracy. After obtaining individualized models on the study sample, we well then apply data-driven clustering algorithms to identify subgroups of participants that share top features of individual pain variability (Aim 2a) and relate these clusters to underlying biological mechanisms implicated in cLBP+MDD (emotion bias and reward processing with concurrent EEG and laboratory measures of central sensitization) (Aim 2b). We hypothesize that unique phenotypes will emerge characterized by shared features of individual pain variability and that empirically-derived phenotypes will be related to distinct biological mechanisms. This application holds promise to make a major contribution to the scientific knowledge of both intra- and inter-individual pain variability in persons with cLBP+MDD. This approach represents a shift in current research practices, which has largely focused on analysis at the group level, by taking a data-driven approach to elucidate individual differences in cLBP+MDD. Further, our clustering approach in Aim 2 is highly novel, which groups individuals based on top features of individual pain variability, enabling a high precision method of identifying homogenous subgroups and examining putative underlying mechanisms of cLBP+MDD subtypes.

NIH Research Projects · FY 2026 · 2025-05

Abstract Glaucoma causes irreversible, progressive vision loss via axon injury and subsequent cell death of retinal ganglion cells (RGCs). Current treatments aim to lower intraocular pressure, although this is insufficient in some patients and associated with complications in others. As such, it is proposed herein to develop complementary strategies to mitigate axon injury signaling. From previous high-throughput functional genomic screens in RGCs, dual leucine zipper kinase (DLK) and its paralog, leucine zipper kinase (LZK), emerged as central players in the cell-autonomous pathway causing cell death following axon injury via upstream regulation of JUN N-terminal kinase 1-3 (JNK1-3). Despite DLK/LZK’s role as master regulators of RGC cell death following injury, their regulation is poorly understood. Further investigation of DLK and its interactions has the potential to reveal the upstream regulatory mechanisms involved in RGC death and thus, additional therapeutic targets. In an additional high throughput screen of the entire kinome in mouse RGCs, the thousand and one (TAO) kinases, specifically TAOK1 and TAOK2, surfaced as key mediators of cell death. Combined knockouts of Taok1 and Taok2 promoted robust and sustained RGC survival in the mouse optic nerve crush (ONC) model. The central hypothesis of this proposal is that TAOK1/2 work as regulators of the DLK/LZK/JNK signaling axis and mediate neuronal cell death in response to axon injury. This hypothesis will be studied in a rodent model and in human stem cell-derived RGCs using pharmacological and viral-based tools combined with CRISPR/Cas9 gene editing to produce loss- and gain-of-functions. Aim 1 will elucidate the relationship between the TAO kinases and DLK/LZK/JNK in axon injury signaling, by genetically probing the upstream/downstream relationship of these key kinases in vitro and in vivo in mice. Aim 2 will explore the role of TAO kinases in cell death signaling using an in vitro model of human RGCs. If successful, the work proposed herein will shed light on the role of the TAO kinases in the pathway responsible for RGC death in a mouse model and in human stem cell-derived RGCs. The neuroprotective potential of TAO kinase inhibition has yet to be fully understood and could be leveraged to mitigate RGC death and vision loss in glaucoma. Furthermore, with the completion of Aim 1, the principal investigator will acquire new skills in adenovirus and AAV production, histological and functional measures of RGC neuroprotection, and viral/CRISPR-based approaches to manipulating gene function. With the completion of Aim 2, the principal investigator will acquire new skills in human stem cell culture and RNA sequencing. The principal investigator will greatly benefit from working under the direct supervision of the sponsor on this proposal, Dr. Derek Welsbie, an expert in glaucoma and DLK/LZK signaling, and the co-sponsor, Dr. Karl Wahlin, an expert in the directed differentiation of stem cells into retinal tissue. Advisement from a committee of experts in the field, continued coursework and access to core facilities at UC San Diego will also be a boon to his training and efforts.

NIH Research Projects · FY 2025 · 2025-05

PROJECT SUMMARY The Sanford Consortium for Regenerative Medicine (SCRM) was formed with the goal of catalyzing collaborations by building and operating a new stem cell research facility that houses inter-institutional and multi- disciplinary scientific laboratories. It draws together under the same roof researchers from five major institutions: UC San Diego, The Salk Institute, The La Jolla Institute for Immunology, The Sanford Burnham Prebys Medical Discovery Institute, and Scripps Research. Shared resources play a significant role in allowing these research collaborations to advance. The Human Embryonic Stem Cell Core Facility (HESCCF) is the largest of the three shared facilities at SCRM and the largest flow cytometry core facility at UC San Diego. Its mission is to provide its users with research space and high-end equipment, which include flow cytometry, electrophysiology, and various imaging platforms. There has been an increase in demand for a modern, state-of-the-art flow cytometer, the top choice being the full-spectrum Cytek Aurora model. In particular, users are showing an interest in expanding their flow cytometry staining panels to analyze 40 plus parameters and be equipped with 96-well plate high-throughput screening. This is well beyond the parameter channel limit of even our most well-equipped analyzer, the BD Fortessa X20. This is an unmet need for all UC San Diego researchers, as all shared flow cytometry facilities in the area are either a) limited by maximum number of lasers and color emission channels; b) unavailable to UC San Diego researchers; or c) the rates are too high for external users. The high demand for this emerging technology is also evident from the equipment in neighboring labs and cores, most of which are still equipped with standard flow cytometry analyzers without high throughput sampling, and not the more evolved full-spectrum analyzers with multi-well plate sample acquisition. The purpose of this grant is to address the need for a shared core facility full-spectrum analyzer that will serve the needs of all five SCRM member institutions. We propose to use the funding from this application to purchase a Cytek Aurora (5 lasers, 63 parameters, 96 well plate high-throughput sample acquisition system). The new instrument will be located in the main section of the HESSCF. The intent is for this analyzer to be exclusively available to researchers interested in analyzing all complexity of multiparametric staining panels and fluorescent proteins, but especially high parameter panels and samples exhibiting FRET. The HESCCF has demonstrated a commitment to the advancement of all research at the Sanford Consortium for Regenerative Medicine. We strive to continue to provide necessary resources, technical expertise, and research space. With the support of our institution and our qualified staff we ensure that the Cytek Aurora will be maintained and used to its full potential.

NIH Research Projects · FY 2026 · 2025-05

Project Summary As the United States continues to experience growth in both homelessness and drug overdose deaths among this population, many urban municipalities have instituted new programs aimed at reducing the visibility of homelessness, including street encampments. These programmatic measures include police- enforced involuntary displacement and temporary rapid shelters such as “safe camping” sites, so-called “tiny homes”, and motel room accommodations. While limited research has shown that some of these programs may negatively impact the health of unhoused people who use drugs (PWUD), little is known about how they may ultimately impact overdose risk and incidence. This proposed study seeks to contribute new knowledge about this association using a sequential mixed methods approach in three phases. In Aim 1, I will use secondary data from the La Frontera cohort study in a longitudinal analysis of involuntary displacement and housing program exposures on overdose outcomes; in Aim 2, I will qualitatively explore these associations and gather participant opinions on how housing programs could be improved via 60 in-depth interviews with 30 PWUD and 30 professional key informants; in Aim 3, I will collate data from the previous two aims alongside published literature to construct a mathematical model to predict future overdose incidence across several potential scenarios. I am a well-qualified candidate with the skills to undertake the proposed research and associated training. I have a strong background in both qualitative and quantitative work. During the course of the five-year award period, I will undertake five training goals: 1) gain expertise in the epidemiology of drug overdose, 2) build skills in the design and conduct of mixed methods studies, 3) acquire training in mathematical modeling of epidemics and overdose, 4) obtain expertise in the ethical conduct of research with marginaliz ed and vulnerable populations, and 5) further build my professional career development skills that will prepare me for a career as an independent academic researcher. To achieve these training goals and complete the proposed research, I have assembled a team of mentors and contributors with expertise and career accomplishments in all training areas – substance use and overdose epidemiology, mixed-methods research, mathematical modeling of infectious disease, and research ethics with vulnerable populations. Under the guidance of my mentorship team, I will engage in activities including coursework at UCSD, workshops and seminars at multiple external institutions, submit to and attend both national and international conferences, and conduct the proposed research. Few researchers possess expertise in these combined topical and methodological areas, and completion of this work will contribute significantly to our understanding of how homelessness programming and policy influences overdose risk. These findings may help shape future evidence-based programming and policy efforts.

NIH Research Projects · FY 2025 · 2025-05

Project Summary The process by which tau moves from its soluble form to neurofibrillary tangles has been studied for many years, but only recently has the importance of an intermediate liquid-liquid phase separation step been shown. Indeed, the assortment of tau into these biomolecular condensates is increasingly seen as a key feature underlying both normal cell function and disease. These liquid-liquid phase separations often proceed liquid-to-solid phase transitions that in turn lead to the protein aggregates underlying tau protein misfolding diseases including Alzheimer’s disease. While the community can observe neurofibrillary tangles using thioflavin T and early-stage biomolecular condensates with FRET, there is no single imaging approach that can map and measure tau in its all three forms in living cells: soluble, liquid-liquid phase separation, and liquid-solid phase separation forms. This work will solve this major limitation with a peptide- based probe specific to tau and aggregation-induced emission (AIE). In AIE, a molecule analogous to a fluorophore produces light proportional to the degree of molecular sequestration and restricted movement. Signal is “off” when the molecule is “floppy” and “on” when locked in place. The use of AIE is significant, innovative, and critical here because the AIE signal will directly measure tau as it becomes compressed into increasingly confined environments (monomers to liquid condensates to fibrillary aggregates). Thus, our testable hypothesis is that fluorescence will increase with the type of condensate: soluble<liquid- liquid<liquid-solid. Aim 1 of the work will build and characterize the probe. We will test the probe with different concentrations of recombinant tau including different tau isoforms, different degrees of tau phosphorylation, and tau from different species. Aim 2 will use the probe in cultured cells (Aim 2A) and histology sections of rodent brains (Aim 2B). We will transfect cells to overexpress tau, induce tau biomolecular condensate and fibril formation, and then map and measure the location of tau forms in these cells using confocal microscopy. The PS19 animal model is available “off the shelf” and will used with histology to understand the distribution of tau BMCs in different brain regions; we will also stain the nuclear pore complex to understand the interactions of these different tau condensates with the nucleus. The significance of the work is apparent by the grave impact Alzheimer’s disease has on society. Innovation is underscored by the ability to image tau across multiple domains of condensation, the ability to map tau condensate interactions with other organelles, and the use of AIE to monitor tau molecular movement. Finally, the probe uses a peptide with known specificity to tau in contract to gold standard probes like thioflavin T. This work is feasible because of the PI’s expertise in imaging agents, peptide probes, and cell and animal models; the Co-I’s expertise in tau pathologies; and our peer-reviewed preliminary data.